Seoul National University · 医療専門職
Professor Changbum R. Ahn's research lab specializes in advancing construction safety, operational efficiency, and environmental sustainability through wearable sensing technologies and data-driven analytics. The lab focuses on leveraging real-time physiological and motion data—collected via low-cost sensors like accelerometers and wearable biometrics—to assess worker fall risk, detect latent safety hazards, and optimize equipment performance. A key research direction involves integrating gait stability metrics such as maximum Lyapunov exponents and operational efficiency models to quantify and reduce air pollutant emissions from construction activities. The lab also emphasizes practical, economically feasible solutions for heterogeneous equipment fleets and real-world construction sites.
Figures are computed from collected data and may differ slightly.
The advent of wearable sensing technologies has produced unprecedented opportunities for the near real-time collection and analysis of workers’ safety and health data. To encourage the proactive safety management these opportunities present, extensive research efforts have explored using various wearable sensing technologies—including motion sensors (e.g., inertial measurement units) and physiological sensors (e.g., heart-rate sensors, electrodermal-activity sensors, skin-temperature sensors, ey
In construction worksites, slips, trips, and falls are major causes of fatal injuries. This fact demonstrates the need for a safety assessment method that provides a comprehensive fall-risk analysis inclusive of the effects of physiological characteristics of construction workers. In this context, this research tests the usefulness of the maximum Lyapunov exponents (Max LE) as a metric to assess construction workers’ comprehensive fall risk. Max LE, one of the gait-stability metrics established
Monitoring the operational efficiency of construction equipment offers great opportunities to enhance not only the productivity but also the environmental performance of construction operations. However, existing enabling technologies still suffer from a lack of economic feasibility, as well as technological compatibility with equipment fleets that are outdated or that consist of diverse manufacturers’ models. In this context, this paper examines the feasibility of measuring the operational effi
Current construction hazard identification mostly relies on safety managers’ ability to identify hazards using their prior knowledge about them. Consequently, numerous latent hazards remain unidentified, which poses significant risks to construction workers. To advance current hazard identification capabilities, this study examines the feasibility of harnessing and analyzing collective patterns of workers’ bodily responses (balance, gait, etc.) to identify safety hazards on a jobsite. To test th
Construction operations generate significant air pollutant emissions, including carbon emissions and diesel exhaust emissions. Controlling operational efficiency is the most important strategy for reducing air pollutants emitted from construction operations. However, current practices to assess air pollutant emissions from construction operations tend to ignore the variability of the operational efficiency that results from different resource allotting and scheduling. In this context, this paper
In the building and construction sector, most efforts related to sustainable development have concentrated on the environmental performance of the operation of buildings and infrastructure. However, several studies have called for the need to mitigate the considerable environmental impacts, especially air pollutant emissions and energy consumption, generated by construction processes. To provide a point of reference for initiating the development of environmentally sustainable construction proce
Repeated exposure to hazards in road construction work zones often generates worker habituation to risks associated with those hazards, a key causal factor in workplace accidents. Understanding the developmental process of risk habituation and providing effective intervention are thus critical to preventing fatalities in road construction work zones. To this end, this study investigates the efficacy of virtual reality (VR) as a behavioral intervention tool to mitigate a decline in vigilant behav
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